Senior Data Scientist – Healthcare Analytics

Ensora Health provides software and services for mental and behavioral health therapists, including practice management, electronic medical records, e-prescribing, billing, and AI-enabled healthcare solutions. The Senior Data Scientist will analyze complex healthcare datasets, develop predictive and statistical models, and deliver actionable insights that improve patient outcomes, optimize clinical workflows, and support AI-powered healthcare applications.

Responsibilities:

• Advanced Statistical Modeling: Apply rigorous statistical techniques (regression, hypothesis testing, survival analysis) to healthcare data for predictive and prescriptive analytics
• Time Series Analysis: Develop models for forecasting and anomaly detection in longitudinal healthcare data (e.g., patient vitals, treatment timelines)
• Feature Engineering: Design and implement robust feature extraction and transformation pipelines for structured and unstructured healthcare data
• Large-Scale Data Handling: Work with high-volume datasets from EHRs, claims, and sensor data using distributed computing frameworks (Spark, Dask)
• Predictive Modeling: Build and validate machine learning models for risk stratification, disease progression, and patient engagement
• Data Quality & Governance: Ensure compliance with healthcare data standards (HIPAA, HL7, FHIR) and maintain data integrity
• Visualization & Communication: Create compelling dashboards and visualizations to communicate insights to clinicians and business stakeholders
• Collaboration: Partner with product managers, engineers, and clinical experts to translate business needs into data-driven solutions

Requirements:

• • Education: Master's or Ph.D. in Statistics, Data Science, Computer Science, or related field
• • Experience: 5+ years in data science roles, with at least 2 years in healthcare analytics
• • Statistical Expertise: Strong knowledge of regression models, Bayesian methods, and hypothesis testing
• • Time Series & Forecasting: Hands-on experience with ARIMA, Prophet, or deep learning-based time series models
• • Programming Skills: Proficiency in Python (pandas, NumPy, scikit-learn), SQL, and experience with PostgreSQL or similar databases
• • Big Data Tools: Experience with Spark, Hadoop, or cloud-based data platforms (AWS, Azure, GCP)
• • Feature Engineering: Proven ability to design features for complex healthcare datasets
• • Domain Knowledge: Familiarity with clinical terminologies, EHR systems, and healthcare workflows